Fragestellung: “Die Manschafft, die zur Halbzeit vorne liegt, gewinnt mit einer 75% Chance auch das Spiel. Falls zur Halbzeit unentschieden ist, gewinnt eher das Heimteam.”

Dafür nehmen wir den Datacamp Datensatz Soccer Data

Als Einführung werden wir auf Datacamp folgende Kurse durchgehen:

# Bibliotheken importieren
library("plotly")
library("plyr")
# List files in Data folder
files <- list.files(path="./Data/", pattern=NULL, all.files=FALSE, full.names=TRUE)

# Create DataFrame with all csv from 2015-2019
df <- ldply(.data = files, .fun = read.csv)

# View entire DataFrame in R Studio
#View(df)
htr_table <- df %>%
    count(HTR)

ftr_table <- df %>%
    count(FTR)

Results = c("Away", "Draw", "Home")
HT_count <- c(htr_table$n)
FT_count <- c(ftr_table$n)

df_results <- data.frame(Results, HT_count, FT_count)

fig <- plot_ly(
  df_results, x = ~Results, y = ~HT_count, type = 'bar', name = 'Half Time Score') %>% 
  add_trace(y = ~FT_count, name = 'Full Time Score') %>%
  layout(yaxis = list(title = 'Count'), barmode = 'group')

fig
NA
# HTR & FTR in einer Spalte zusammenfügen

df$result <- paste(df$HTR, df$FTR)

df_count_results <- df %>% 
  group_by(result) %>% 
  summarise(count_result = n() / nrow(df) * 100)

df_count_results %>%
  plot_ly(x = ~reorder(result, count_result), y = ~count_result) %>%
  add_bars() %>%
  layout(xaxis = list(categoryorder = "total descending", title = "Game Progress"),
         yaxis = list(title = "Probability"),
         title = "What is the probability of a game progress?")
NA
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